1. Field of the Invention
This invention generally relates to managing information in a database, and in particular, it relates to methods for determining the accuracy of linked relationships in a database.
2. Related Art
Customers often have more than one account established through a business, especially with a service-oriented business such as a financial services company or an insurance business. In the case of the financial services industry, for example, a single customer may have any combination of a personal bank account, a mortgage, a line of credit (such as a home equity line of credit), a personal credit card, a business credit card, a rewards account, and one or more investment accounts with a single financial institution. In the insurance business, a single customer may have any combination of health insurance, auto insurance, home owners insurance, and other kinds of insurance protection as well. Even with non-service businesses, a single customer may have multiple accounts. For example, a single customer may have one account with a computer supply company for home purchases and another account with the same company for small business purchases.
It is important for a company to recognize that all of the customer's accounts belong to a single customer and to link those accounts, in order to appropriately market to the customer without overloading the customer. Further, ensuring that all accounts for a given customer are, in fact, accurately associated with that customer is vital for businesses that offer risk management and decision-support to their customers. The correct linking of accounts with a customer can improve the accuracy of the financial company's estimate of the financial status of the customer.
In practice, accurately linking accounts with a single customer proves to be a non-trivial undertaking. It is possible to associate one or more accounts with a single customer based on unique customer identifying information, such as the customer name, social security number, date of birth, address, and other distinctive or unique identifiers. However, the association process is fallible, as it is possible that variations may creep into the way a customer's name or address is recorded, or simply that errors are made during the process of collecting customer identifying data. People change addresses over time, or change their name, which can thwart efforts to make account associations based on the name, address, or other time-variant identification data.
Still another factor which makes it difficult to effectively recognize which accounts are, in fact, associated with a single customer is the size of many businesses. A large service business, such as a large financial institution, may have multiple business units. Often, these business units do not efficiently or effectively share information, since in some cases data processing may be distributed over multiple computer systems and software systems. As a result customer information can be fragmented over these multiple data processing systems and their associated databases.
The difficulties inherent to the linking process often result in errors in the linking process. For example, it is possible that that accounts which actually belong to two separate customers may become associated, within the business database, with a single customer and thus be incorrectly linked. Further, it may also be possible that two accounts belonging to a single customer may not be associated with that customer in the business database.
Therefore, it is essential to businesses, such as the financial services industries, to identify the linking errors present in their associated databases and identify and address the underlying causes of these linking errors. However, existing techniques are generally incapable of providing accurate estimates of the linking errors within business databases and a detailed understanding of the causes of these errors.